This repository contains the python code for our AISTATS 2022 paper Near Instance Optimal Model Selection for Pure Exploration Linear Bandits. Packages used include: numpy, sys, multiprocessing, pickle, time, logging and matplotlib.
Let x = 0 (for experiment in Section 7) or x = 1 (for experiment in Appendix F, we also set max_iter = 500 in algs_class.py in this experiment). Use the following commands to reproduce our experiments.
python3 run_algs.py x
python3 plot.py x
On a cluster consists of two Intel® Xeon® Gold 6254 Processors, the runtime for experiment in Section 7 is around 20 minutes and the runtime for experiment in Appendix F is around 4.5 hours.
Part of the code is obtained/adapted from GitHub - fiezt/Transductive-Linear-Bandit-Code. We thank authors of Sequential Experimental Design for Transductive Linear Bandits for their open-source code. We include a copy of their License in folder LICENSE_OTHERS.